Mitochondria as the powerhouses of sexual selection: testing mechanistic links between development, cellular respiration, and bird song

Although the influence of developmental conditions on the expression of sexually selected traits is established, the physiological mechanisms that modulate such effects remain a matter of intense debate. Here, we test the role of the developmental environment in shaping adult mitochondrial function and link mitochondrial function to expression of a sexually selected trait in males (bird song). We exposed male zebra finches (Taeniopygia guttata) to corticosterone (CORT) treatment during development. After males reached adulthood, we quantified mitochondrial function from whole red blood cells and measured baseline CORT and testosterone levels, body condition/composition, and song structure. CORT-treated males had less efficient mitochondrial function (FCRL/R), lower mitochondrial ‘working pace’ (FCRR/ETS), and higher baseline levels of CORT as adults compared to control males. Using structural equation modelling, we found that the effects of CORT treatment during development on adult mitochondrial function were indirect and modulated by baseline CORT levels, which are programmed by CORT treatment during development. Developmental treatment had an indirect effect on song peak frequency. Males treated with CORT during development sang songs with higher peak frequency than control males, but this effect was modulated through increased CORT levels and decreased mitochondrial efficiency (FCRL/R). CORT-treated males had smaller tarsi compared to control males; however, there were no associations between body size and measures of song frequency. Here, we provide the first evidence supporting links between the developmental environment, mitochondrial function, and the expression of a sexually selected display (bird song).

Aerosol Exposure of Cynomolgus Macaques to SARS-CoV-2 Results in More Severe Pathology than Existing Models

The emergence of SARS-CoV-2 pandemic has highlighted the need for animal models that faithfully recapitulate the salient features of COVID-19 disease in humans; these models are necessary for the rapid down-selection, testing, and evaluation of medical countermeasures. Here we performed a direct comparison of two distinct routes of SARS-CoV-2 exposure, combined intratracheal/intranasal and small particle aerosol, in two nonhuman primate species: rhesus and cynomolgus macaques. While all four experimental groups displayed very few outward clinical signs, evidence of mild to moderate respiratory disease was present on radiographs and at the time of necropsy. Cynomolgus macaques exposed via the aerosol route also developed the most consistent fever responses and had the most severe respiratory disease and pathology. This study demonstrates that while all four models were suitable representations of mild COVID-like illness, aerosol exposure of cynomolgus macaques to SARS-CoV-2 produced the most severe disease, which may provide additional clinical endpoints for evaluating therapeutics and vaccines.

Algorithm of combining chromatography mass spectrometry-untargeted profiling and multivariate analysis for identification of marker-substances in samples of complex composition

A viral development of statistical data processing, computing capabilities, chromatography-mass spectrometry, and omics technologies (technologies based on the achievements of genomics, transcriptomics, proteomics, metabolomics) in recent decades has not led to formation of a unified protocol for untargeted profiling. Systematic errors reduce the reproducibility and reliability of the obtained results, and at the same time hinder consolidation and analysis of data gained in large-scale multi-day experiments. We propose an algorithm for conducting omics profiling to identify potential markers in the samples of complex composition and present the case study of urine samples obtained from different clinical groups of patients. Profiling was carried out by the method of liquid chromatography mass spectrometry. The markers were selected using methods of multivariate analysis including machine learning and feature selection. Testing of the approach was performed using an independent dataset by clustering and projection on principal components.

Synonymous Site-to-Site Substitution Rate Variation Dramatically Inflates False Positive Rates of Selection Analyses: Ignore at Your Own Peril

Most molecular evolutionary studies of natural selection maintain the decades-old assumption that synonymous substitution rate variation (SRV) across sites within genes occurs at levels that are either nonexistent or negligible. However, numerous studies challenge this assumption from a biological perspective and show that SRV is comparable in magnitude to that of nonsynonymous substitution rate variation. We evaluated the impact of this assumption on methods for inferring selection at the molecular level by incorporating SRV into an existing method (BUSTED) for detecting signatures of episodic diversifying selection in genes. Using simulated data we found that failing to account for even moderate levels of SRV in selection testing is likely to produce intolerably high false positive rates. To evaluate the effect of the SRV assumption on actual inferences we compared results of tests with and without the assumption in an empirical analysis of over 13,000 Euteleostomi (bony vertebrate) gene alignments from the Selectome database. This exercise reveals that close to 50% of positive results (i.e., evidence for selection) in empirical analyses disappear when SRV is modeled as part of the statistical analysis and are thus candidates for being false positives. The results from this work add to a growing literature establishing that tests of selection are much more sensitive to certain model assumptions than previously believed.

Naive Bayes Algorithm Using Selection of Correlation Based Featured Selections Features for Chronic Diagnosis Disease

Chronic kidney disease is a disease that can cause death, because the pathophysiological etiology resulting in a progressive decline in renal function, and ends in kidney failure. Chronic Kidney Disease (CKD) has now become a serious problem in the world. Kidney and urinary tract diseases have caused the death of 850,000 people each year. This suggests that the disease was ranked the 12th highest mortality rate. Some studies in the field of health including one with chronic kidney disease have been carried out to detect the disease early, In this study, testing the Naive Bayes algorithm to detect the disease on patients who tested positive for negative CKD and CKD. From the results of the test algorithm accuracy value will be compared against the results of the algorithm accuracy before use and after feature selection using feature selection Featured Correlation Based Selection (CFS), it is known that Naive Bayes algorithm after feature selection that is 93.58%, while the naive Bayes without feature selection the result is 93.54% accuracy. Seeing the value of a second accuracy testing Naive Bayes algorithm without using the feature selection and feature selection, testing both these algorithms including the classification is very good, because the accuracy value above 0.90 to 1.00. Included in the excellent classification. higher accuracy results.

Estimation of Sunflower Yields at a Decametric Spatial Scale—A Statistical Approach Based on Multi-Temporal Satellite Images

Recent advances in sensors onboard harvesting machines allow accessing the intra-plot variability of yields, spatial scale fully compatible with numerous on-going satellite missions. The aim of this study is to estimate the sunflower yield at the intra-plot spatial scale using the multi-temporal images provided by the Landsat-8 and Sentinel-2 missions. The proposed approach is based on a statistical algorithm, testing different sampling strategies to partition the dataset into independent training and testing sets: A random selection (testing different ratio), a systematic selection (focusing on different plots) and a forecast procedure (using an increasing number of images). Emphasis is put on the use of high spatial and temporal resolution satellite data acquired throughout two agricultural seasons, on a study site located in southwestern France. Ground measurements consist in intra-plot yields collected by a surveying harvesting machine with GPS system on track mode. The forecast of yield throughout the agricultural season provides early accurate estimation two months before the harvest, with R2 equal to 0.59 or 0.66 and root mean square error (RMSE) of 4.7 or 3.4 q ha−1, for the agricultural seasons 2016 and 2017 respectively. Results obtained with the random selection or the systematic selection will be developed later, in a longer paper.

Principles for the Validation and Use of Personnel Selection Procedures

The Society for Industrial and Organizational Psychology (SIOP) is pleased to offer the fifth edition of the Principles for the Validation and Use of Personnel Selection Procedures, which was approved by the APA Council of Representatives in August 2018 as an authoritative guidelines document for employee selection testing and an official statement of the APA. Over a three-year period, the Principles Revision Committee updated this document from the fourth edition to be consistent with the 2014 Standards for Educational and Psychological Testing, invited commentary from SIOP and APA that informed subsequent revisions, and solicited a thorough legal review.

Psychological Measurement: Critical Analysis of Psychological Testing in Personnel Selection

<p>This paper examines the importance of psychological testing in personnel selection. Selection is a process of hiring the job applicant who will be most successful in meeting job demands. Poor hiring can be costly to an organisation, thus, they rely on different techniques of selection, testing is the most commonly used. An attempt is made to understand the history of testing, use of testing in selection procedure, and various kinds of test used with main emphasis on the cognitive ability and personality testing. It also attempts to critically analyse some of the issues associated with testing, with emphasis on the validity and utility of tests. The issue of cultural fairness, biases and discrimination has also been explored.</p>